A customer self-help system is a system that supports or accompanies one or more other software systems by helping users of the one or more other software systems find answers to their questions, without involving live customer support personnel. If a customer self-help system adequately helps a user find a satisfactory answer to the user's question, the user is less likely to seek addition support from live customer support (e.g., telephone support, live chat, text message, etc.). A business benefit of a well-functioning customer self-help system is reduced overhead costs for a company because providing live customer support can be expensive (e.g., sometimes costing as much as $25 per use of the live customer support). A user benefit of a well-functioning customer self-help system is that users can find answers to their questions more quickly than having to wait for live customer support because use of live customer support usually involves waiting in a queue for a turn to communicate with a customer support representative.
Traditional customer self-help systems use content searching methods that employ content prioritization techniques. In some cases, these prior art prioritization techniques inadequately match available customer support content with user search queries. In particular, traditional customer self-help systems prioritize the relevance of customer support content based on the creation date (e.g., file creation date) of the customer support content. Consequently, newer customer support content (e.g., user experience pages) are prioritized over older customer support content. While this approach could be used to prioritize some customer support content (e.g., product features), such an approach is less appropriate for customer support content that does not change very often (e.g., tax laws or regulations). In other words, such an approach might de-prioritize customer support content that is the most relevant to a search query because the age of the customer support content is older than newer customer support content, leading to search results that are not relevant or most relevant to a user's search query.
A problem with failing to provide users with information that is relevant or most relevant to their search query is that the customer self-help system may appear useless, e.g., be irrelevant, to the users. If a user enters a search query and does not obtain search results that are expected or that answer the user's question, then the user may continue to feel concerned about one or more aspects of the financial management system that led the user to submitting a search query in the first place. A natural result is that the user will lose trust in the customer self-help system and possibly in any financial management systems associated with the customer self-help system.
Another problem with failing to provide users with information that is relevant or most relevant to their search query is that the customer self-help system may fail to capitalize on becoming a trusted source of information for users. For example, if a media outlet (e.g., AARP®, CNN®, Financial Times®, etc.) makes an announcement that is related to obtaining a particular financial advantage (e.g., based on a change to tax laws), users who search a customer self-help system for more information about the announcement may recognize the customer self-help system as a trusted source of information. However, users who receive search results that appear to be oblivious to the announcement may be disappointed and look elsewhere for guidance, both for the current situation and for future issues.
Another problem associated with failing to provide users with information that is relevant or most relevant to their search query is that the customer self-help system may be providing users with the faulty (e.g., out-dated) instructions. For example, if a customer self-help system provides a user with information on how to address a particular product error, even though the product error has been resolved, then the user is essentially being instructed to perform one or more unnecessary steps to address a problem that is no longer relevant.
Traditional content searching techniques include associating the relevance of searchable customer support content with the age of customer support content, but the age of the customer support content is not necessarily the dominant characteristic that determines whether the customer support content is relevant or highly relevant at a given point in time. Thus, a technical problem that exists for customer self-help systems and search engines is a need to avoid providing less-relevant or irrelevant search results due to poor prioritization of customer support content.